Andrew X StewartBoard member; Researcher at NextSense
Think tank · Research orgs · Berkeley, CA · Est. 2019
Convergence Analysis is a U.S.-based nonprofit research and policy organization focused on AI existential-risk strategy, transformative-AI scenario planning, and governance recommendations. Its mission is to “design a safe and flourishing future for humanity in a world with transformative AI,” with work organized around (1) scenario research to model plausible trajectories and risks, (2) governance research to develop concrete policy recommendations aimed at mitigating catastrophic outcomes, and (3) AI awareness efforts intended to inform policymakers and the broader public.
Institutionally, Convergence positions itself as a “foundational series of sociotechnical reports” on key AI scenarios and governance recommendations, aiming to influence decision-making by grantmakers, policymakers, and the AI safety community. Strategically, the organization has emphasized governance implementation details—e.g., work on model registries, AI chip registration policies, and emergency preparedness—alongside broader framing and field-building initiatives such as Threshold 2030 (co-hosted with Metaculus and the Future of Life Institute).
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We conduct strategic research and advocate for critical governance interventions to mitigate the existential risk posed by AI technologies.
Convergence 2024 Impact ReviewWe conduct strategic research and advocate for critical governance interventions to mitigate the existential risk posed by AI technologies.
Conference Summary: Threshold 2030 - Modeling AI Economic FuturesWe conduct strategic research and advocate for critical governance interventions to mitigate the existential risk posed by AI technologies.
New Report: 2024 State of the AI Regulatory LandscapeWe conduct strategic research and advocate for critical governance interventions to mitigate the existential risk posed by AI technologies.
New Report: Evaluating an AI Chip Registration PolicyWe conduct strategic research and advocate for critical governance interventions to mitigate the existential risk posed by AI technologies.
Announcing Convergence Analysis: An Institute for AI Scenario & Governance ResearchWe conduct strategic research and advocate for critical governance interventions to mitigate the existential risk posed by AI technologies.
The AI Readiness Objectives Towards Sufficiency in National AI Security StrategiesWe conduct strategic research and advocate for critical governance interventions to mitigate the existential risk posed by AI technologies.
Pathways to short TAI timelinesThis report explores pathways through which transformative AI (TAI) could be developed within the next ten years (‘short TAI timelines’). It examines compute scaling and recursive improvement as key mechanisms for AI capabilities progress, describes seven distinct scenarios with
The Manhattan Trap Why a Race to Artificial Superintelligence is Self-DefeatingThis paper examines the strategic dynamics of international competition to develop Artificial Superintelligence (ASI).
Training Data Attribution (TDA) Examining Its Adoption & Use CasesTDA techniques aim to identify training data points that are especially influential on the behavior of specific model outputs. This report investigates Training Data Attribution (TDA) and its potential importance to and tractability for reducing extreme risks from AI.
Analysis of Global AI Governance StrategiesWe analyze three prominent strategies for governing transformative AI (TAI) development: Cooperative Development, Strategic Advantage, and Global Moratorium. We evaluate these strategies across varying levels of alignment difficulty and development timelines, examining their effe
The brave new world of AI Implications for public sector agents, organisations, and governanceWe conduct strategic research and advocate for critical governance interventions to mitigate the existential risk posed by AI technologies.
Convergence published a framework proposing seven AI readiness objectives and argues governments that achieve adequacy across these areas will be sufficiently prepared to securely harness powerful AI systems.
Convergence Fellowship Program: Meeting the AI Workforce ChallengeA policy brief proposing a roadmap for federal and youth-focused local actions to prepare for AI-driven workforce transformation, framed around equity and sustainable development.
Convergence Fellowship Program: Toward ASI Stability (Treaty Framework for U.S.–China Cooperation)A project exploring a phased, enforceable treaty concept between the U.S. and China to reduce the risk of a dangerous race toward Artificial Superintelligence.
Convergence Fellowship Program: Decoding AI Diffusion (AI Diffusion: Mapping the Path of Transformative AI across Industries)A report introducing a framework for assessing how transformative AI adoption may differ across economic sectors, including factors that accelerate or impede adoption.
Convergence 2024 Impact ReviewA retrospective describing Convergence’s 2024 outputs and claimed impacts, including publication volume, contributions to regulatory frameworks, and outreach.
Conference Summary: Threshold 2030 – Modeling AI Economic FuturesA conference report and summary output capturing scenario and modeling work around how AI timelines could affect economic outcomes by 2030.